Syndemic profiles of people living with hepatitis C virus using population-level latent class analysis to optimize health services. (November 2020) - Clementi, Emilia; Bartlett, Sofia; Otterstatter, Michael; Buxton, Jane A.; Wong, Stanley; Yu, Amanda; Butt, Zahid A.; Wilton, James; Pearce, Margo; Jeong, Dahn; Binka, Mawuena; Adu, Prince; et al.
Highlights: Syndemics are combinations of co-occurring epidemics and large-scale social forces. Hepatitis C virus infection affects diverse populations. Hepatitis C virus coexists with other chronic infections and mental health issues. Latent Class Analysis can allow for the empirical characterization of syndemics. Characterization of syndemic groups can help design a suite of hepatitis C services. Abstract: Background: Hepatitis C (HCV) affects diverse populations such as people who inject drugs (PWID), 'baby boomers, ' gay/bisexual men who have sex with men (gbMSM), and people from HCV endemic regions. Assessing HCV syndemics (i.e.relationships with mental health/chronic diseases) among subpopulations using Latent Class Analysis (LCA) may facilitate targeted program planning. Methods: The BC Hepatitis Testers Cohort(BC-HTC) includes all HCV cases identified in BC between 1990 and 2015, integrated with medical administrative data. LCA grouped all BC-HTC HCV diagnosed people(n = 73, 665) by socio-demographic/clinical indicators previously determined to be relevant for HCV outcomes. The final model was chosen based on fit statistics, epidemiological meaningfulness, and posterior probability. Classes were named by most defining characteristics. Results: The six-class model was the best fit and had the following names and characteristics: 'Younger PWID' (n = 11, 563): recent IDU (67%), people born >1974 (48%), mental illness (62%), material deprivation (59%). 'Older PWID' (n = 15, 266): past IDU (78%), HIV (17%), HBV (17%) coinfections, alcohol misuse(68%). 'Other Middle-Aged People' (n = 9 019): gbMSM (26%), material privilege (31%), people born between 1965−1974 (47%). ' P eople of Asian backgrounds' (n = 4718): East/South Asians (92%), no alcohol misuse (97%) or mental illness (93%), people born <1945 (26%), social privilege (66%). 'Rural baby boomers' (n = 20, 401): rural dwellers (32%), baby boomers (79%), heterosexuals (99%), no HIV (100%). 'Urban socially deprived baby boomers' (n = 12, 698): urban dwellers (99%), no IDU (100%), liver disease (22%), social deprivation (94%). Conclusions: Differences between classes suggest variability in patients' service needs. Further analysis of health service utilization patterns may inform optimal service layout.